Musings on Buddhism and modern global culture, plus a few miscellaneous topics.

Sunday, 25 October 2009

Objections to Computationalism and Arguments Against Artificial Intelligence

Beyond the algorithmic constraints

Artificial intelligence (AI) has two aspects, technological and philosophical:

(1) Technological AI
Technological AI is a set of techniques (reducible to algorithms) for simulating some aspect of human intelligence in a machine. The machine is usually a general purpose computer. Whether the intelligence implemented in a machine is capable of doing anything truly novel, or is merely 'canned' procedures following logical tracks and switches, is open to debate. Typical examples of technological AI are expert systems, chess-playing programs and neural networks (which can either be implemented in relay-hardware or modelled in software on a computer).

(2) Philosophical AI or Computationalism
Secondly, and of more relevance to this discussion, is computationalism or philosophical AI, (sometimes also known as Strong AI), which is the view that all human mental activities are reducible to algorithms, and could therefore be implemented on a computer. Computationalism is an essential tenet of materialism, which states that there is no need to assume any spiritual or non-algorithmic aspect to existence.

Computationalism is thus diametrically opposed to Buddhist philosophy, which regards the subtle mind (that which survives death and goes on to the next life) as a fundamental aspect of reality, not an emergent property or epiphenomenon of matter. Buddhism views a sentient being, human or animal and its mind, as a totally different kind of thing from a machine or automaton.

Syntax and Semantics
There are a number of arguments against computationalism . Algorithms do not contain within themselves any meaning. For example, the following two statements reduce to exactly the same algorithm within the memory of a computer

Such considerations have led critics of computationalism to claim that algorithms can only contain syntax, not semantics [SEARLE 1997]. Hence computers can never understand their subject matter. All assignments of meaning to their inputs, internal states and outputs have to be defined from outside the system.

This may explain why the process of writing algorithms does not in itself appear to be algorithmic. The real test of Artificial Intelligence would be to produce a general purpose algorithm-writing algorithm. A convincing example would be an algorithm that could simulate the mind of a programmer sufficiently to be able to write algorithms to perform such disparate activities as predicting the movements of the planet Neptune, controlling an automatic train, regulating a distillation column, and optimising traffic flows through interlinked sets of lights.

According to the computationalist view this 'Mother of all Algorithms' must exist as an algorithm in the programmer's brain, though why and how such a thing evolved is rather difficult to imagine. It would certainly have conferred no selective advantage to our ancestors until the present generation (even so, do programmers outreproduce normal people?).

The proof of philosophical AI would be to program the Mother of all Algorithms on a computer. At present no one has the slightest clue of how to even start to go about producing such a thing.

According to Buddhist philosophy this is hardly surprising, as the Mother of all Algorithms is itself NOT an algorithm and never could be programmed. The mother of all algorithms is the formless mind imputing meaning onto its objects (i.e. imputing meaning on to the sequential and structural components of the algorithm as it is being written).

The non-algorithmic dimension of mind, of understanding of meaning, is needed to turn the user's (semantically expressed) requirements into the purely syntactic structural and causal relationships of the algorithmic flowchart or code.

Finally, deep mathematical criticisms of AI have been made by the physicist Roger Penrose [Penrose 1989] on the basis that there are certain mathematical truths such as Gödel's theorem, which are apparent to a human observer but can never be proved by any algorithm.